Dataset Information

Optic Flow Processing in Patients With Macular Degeneration.

ABSTRACT:

Purpose

Optic flow processing was characterized in patients with macular degeneration (MD).

Methods

Twelve patients with dense bilateral scotomas and 12 age- and gender-matched control participants performed psychophysical experiments. Stimuli were dynamic random-dot kinematograms projected on a large screen. For each component of optic flow (translational, radial, and rotational), we estimated motion coherence discrimination thresholds in our participants using an adaptive Bayesian procedure.

Results

Thresholds for translational, rotational, and radial patterns were comparable between patients and their matched control participants. A negative correlation was observed in patients between the time since MD diagnosis and coherence thresholds for translational patterns.

Conclusions

Our results suggest that in patients with MD, selectivity to optic flow patterns is preserved.

SUBMITTER: Guenot J

PROVIDER: S-EPMC9672899 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optic Flow Processing in Patients With Macular Degeneration.

Guénot Jade J Trotter Yves Y Fricker Paul P Cherubini Marta M Soler Vincent V Cottereau Benoit R BR

Investigative ophthalmology & visual science 20221101 12

<h4>Purpose</h4>Optic flow processing was characterized in patients with macular degeneration (MD).<h4>Methods</h4>Twelve patients with dense bilateral scotomas and 12 age- and gender-matched control participants performed psychophysical experiments. Stimuli were dynamic random-dot kinematograms projected on a large screen. For each component of optic flow (translational, radial, and rotational), we estimated motion coherence discrimination thresholds in our participants using an adaptive Bayesi ...[more]

PMID: 36378131

Similar Datasets

Project description:Flying insects, such as flies or bees, rely on consistent information regarding the depth structure of the environment when performing their flight maneuvers in cluttered natural environments. These behaviors include avoiding collisions, approaching targets or spatial navigation. Insects are thought to obtain depth information visually from the retinal image displacements ("optic flow") during translational ego-motion. Optic flow in the insect visual system is processed by a mechanism that can be modeled by correlation-type elementary motion detectors (EMDs). However, it is still an open question how spatial information can be extracted reliably from the responses of the highly contrast- and pattern-dependent EMD responses, especially if the vast range of light intensities encountered in natural environments is taken into account. This question will be addressed here by systematically modeling the peripheral visual system of flies, including various adaptive mechanisms. Different model variants of the peripheral visual system were stimulated with image sequences that mimic the panoramic visual input during translational ego-motion in various natural environments, and the resulting peripheral signals were fed into an array of EMDs. We characterized the influence of each peripheral computational unit on the representation of spatial information in the EMD responses. Our model simulations reveal that information about the overall light level needs to be eliminated from the EMD input as is accomplished under light-adapted conditions in the insect peripheral visual system. The response characteristics of large monopolar cells (LMCs) resemble that of a band-pass filter, which reduces the contrast dependency of EMDs strongly, effectively enhancing the representation of the nearness of objects and, especially, of their contours. We furthermore show that local brightness adaptation of photoreceptors allows for spatial vision under a wide range of dynamic light conditions.

Dataset Information

Optic Flow Processing in Patients With Macular Degeneration.

Purpose

Methods

Results

Conclusions

Publications

Optic Flow Processing in Patients With Macular Degeneration.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets